The Effects of Two Community-Based Participatory Action Research Programs on Violence Outside of and in School Among Adolescents and Young Adults in a Latino Community.

PURPOSE: Violence is the leading cause of death among adolescents and young adults in the Americas. Community-Based Participatory Action Research engaged youth and parents to develop and implement two interventions. A Violence Prevention Program (VPP) focused on risk factors for violence, and a Positive Youth Development Program (PYDP) focused on protective factors. Program effects on violence outside of and in school were assessed at 6 and 12 months. METHODS: Both interventions included an 8-week internet-based program and an in-person youth summit. Participants were prospectively randomized twice, first to the VPP and a no-VPP control group and again to the PYDP and a no-PYDP control group. Participants self-reported violence outside of and in school through self-administered baseline surveys with repeat assessments at 6 and 12 months. Analysis of covariance models examined VPP and PYDP effects on violence. RESULTS: The analysis sample was 86% Latino, 56% female, 36% aged 10-13 years, 45% aged 14-18, and 19% aged 19-23 years. Analysis of covariance models of violence outside of school demonstrated small program interaction effects at 6 months (partial eta2 = .030; p = .007) and small VPP effects at 12 months (partial eta2 = .023; p = .025). Models of violence in school demonstrated small PYDP effects at 6 months (partial eta2 = .023; p = .018). CONCLUSIONS: Community-Based Participatory Action Research engaging adolescents, young adults, and parents to address locally relevant health issues can have multiple benefits. In this study, a VPP had positive effects on violence outside of school at 12 months, and a PYDP had positive effects on violence in school at 6 months.

Quality of urban runoff in wet and dry seasons: a case study in a semi-arid zone.

Urban runoff (UR) is a promising new resource that may alleviate growing tensions in numerous arid and semi-arid regions of the world. However, it is precisely in these zones that the available UR quality characteristics are scarcer. This work aims to evaluate a wide set of parameters to establish a detailed approach to both the quality of UR in a midsized city in Central Mexico and the feasibility of using UR to recharge aquifers. UR from an institutional land use site was sampled during wet and dry seasons and assessed for suspended solids, organic matter, nutrients, microorganisms, metals, and persistent organic chemicals (i.e., polycyclic aromatic hydrocarbons, PAH). The results were analyzed using multivariate statistical methods to identify relationships among the variables, the sampling sites and the seasons. The soil erosion and the leaching of materials due to the water flow through vegetated areas were identified as the most influencing factor on the quality of the site runoff in both dry and wet seasons. Additionally, data were more heterogeneous during the dry season, and higher pollutant concentrations were found both during the dry season and in more pervious zones. We consider UR a promising water source for recharging aquifers in arid and semi-arid zones if a program is implemented that can integrate an adequate runoff treatment system, soil protection, and other non-structural measures.

Life sciences domain analysis model.

OBJECTIVE: Meaningful exchange of information is a fundamental challenge in collaborative biomedical research. To help address this, the authors developed the Life Sciences Domain Analysis Model (LS DAM), an information model that provides a framework for communication among domain experts and technical teams developing information systems to support biomedical research. The LS DAM is harmonized with the Biomedical Research Integrated Domain Group (BRIDG) model of protocol-driven clinical research. Together, these models can facilitate data exchange for translational research. MATERIALS AND METHODS: The content of the LS DAM was driven by analysis of life sciences and translational research scenarios and the concepts in the model are derived from existing information models, reference models and data exchange formats. The model is represented in the Unified Modeling Language and uses ISO 21090 data types. RESULTS: The LS DAM v2.2.1 is comprised of 130 classes and covers several core areas including Experiment, Molecular Biology, Molecular Databases and Specimen. Nearly half of these classes originate from the BRIDG model, emphasizing the semantic harmonization between these models. Validation of the LS DAM against independently derived information models, research scenarios and reference databases supports its general applicability to represent life sciences research. DISCUSSION: The LS DAM provides unambiguous definitions for concepts required to describe life sciences research. The processes established to achieve consensus among domain experts will be applied in future iterations and may be broadly applicable to other standardization efforts. CONCLUSIONS: The LS DAM provides common semantics for life sciences research. Through harmonization with BRIDG, it promotes interoperability in translational science.